Explanation-based Ranking in Opinionated Recommender Systems

Explanations can help people to make better choices, but
their use in recommender systems has so far been limited to the annota-
tion of recommendations after they have been ranked and suggested to
the user. In this paper we argue that explanations can also be used to
rank recommendations. We describe a technique that uses the strength
of an item's explanation as a ranking signal { preferring items with
compelling explanations { and demonstrate its ecacy on a real-world
dataset.

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